Haifa Use Case – Nightlife activities
This scenario, serving as a basis for WP10, aims to understand the attitudes and preferences of citizens’ towards various journey plans. Stated preference surveys, consisting of PETRA-based journey plans, will provide the basis for these insights. An on-site survey will be conducted on special event and weekends’ evenings in the vicinity of one of Haifa’s popular entertainment areas, and a focus group will be recruited to regularly use PETRA before commuting to the entertainment area and state their preferred travel alternative.
Figure 5 includes a description of the main components and data flows constituting the Use Case. Travelers (interviewees) will provide their origin, transport modes used, expected time for returning journey, basic preferences and basic socio-demographic information. Using a tablet, the surveyor will input this data into an application designed to transfer the data into the PETRA system. PETRA, based on its innovative algorithms and relevant information from Haifa’s open data platform, will then produce alternative routes for the two-way journey (home-entertainment area-home), estimated travel time for each of them and the associated level of reliability.
These alternatives routes will be presented to the interviewee, who in turn will state which alternative would have been the selected one if this information would have been available to them before starting the journey.
The on-site survey will be based on an experiment plan targeting various population groups in terms of age, gender and frequency of traveling to the specific area investigated. This data collection method provides the foundation for analyzing and drawing conclusions regarding the stated preference of different citizens’ groups with regards to various transport modes as well as the perception of reliability index and its effect on the selection of the journey plan. The conclusions drawn can then be used for improving PETRA’s functionality as a travel advisor for end-users.
While the travellers benefit from high quality journey plans’ recommendations, PETRA will also enhance the quality of the city’s traffic management activities. Various congestion scenarios will be developed in accordance with WP3 and WP6. Based on simulation results of these scenarios, appropriate traffic signal programs will be designed as a remedy for such situations. The scenarios will then be extended by incorporating predicted congestion produced by PETRA. Proactive traffic management strategies, in which the new signal programs are implemented prior to the actual evolvement of the congestion, will be developed of the basis of simulating the extended scenarios. These traffic management strategies will reflect the trade-off between type I error, where the congestion was not prevented due to low reliability of the prediction, and type II error, where the proactive strategy is implemented in cases of false congestion alarms. The overall benefits gained in terms of exposure to congestion will be assessed for evaluating the contribution of PETRA to smoother flows in the network.